NB Project: NLRP3 mRNA

Author

Published

June 27, 2024

Code

library(readxl)
library(car)
library(multcomp)
library(ggplot2)
library(writexl)

Code

# Load the data
NB_data <- read_excel("Fold Change Calculations for Final Data_tidy.xlsx", sheet = 5)
data3 <- NB_data

# Display the first few rows of the imported data
head(data3)

# A tibble: 6 × 4
  Sample Gene  Treatment NLRP3_mRNA
   <dbl> <chr> <chr>          <dbl>
1      1 C57   Control         6.45
2      2 C57   LPS             0.03
3      3 C57   Control         5.24
4      4 C57   LPS             0.07
5      5 C57   Control         6.41
6      6 C57   LPS             0.28

Code

# Convert relevant columns to factors (Assuming 'Treatment' and 'Gene' are columns)
data3$Treatment <- factor(data3$Treatment, levels = c(
  "Control", "ATP", "LPS", "LPS+ATP", "LPS+NIG", "NIG"))
data3$Gene <- as.factor(data3$Gene)
head(data3)

# A tibble: 6 × 4
  Sample Gene  Treatment NLRP3_mRNA
   <dbl> <fct> <fct>          <dbl>
1      1 C57   Control         6.45
2      2 C57   LPS             0.03
3      3 C57   Control         5.24
4      4 C57   LPS             0.07
5      5 C57   Control         6.41
6      6 C57   LPS             0.28

Code

# Perform a two-way ANOVA (Assuming 'NLRP3_mRNA' is the dependent variable)
anova_result <- aov(NLRP3_mRNA ~ Treatment * Gene, data = data3)

# Display the summary of ANOVA results
summary(anova_result)

               Df Sum Sq Mean Sq  F value   Pr(>F)    
Treatment       1 169.09  169.09 1670.992 2.97e-14 ***
Gene            2   0.05    0.02    0.235    0.794    
Treatment:Gene  2   0.15    0.08    0.752    0.493    
Residuals      12   1.21    0.10                      
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Code

# Perform Tukey's HSD post-hoc test for multiple comparisons
tukey_result <- TukeyHSD(anova_result)
print(tukey_result)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = NLRP3_mRNA ~ Treatment * Gene, data = data3)

$Treatment
                 diff       lwr       upr p adj
LPS-Control -6.129889 -6.456616 -5.803162     0

$Gene
                   diff        lwr       upr     p adj
APOE4-APOE3 -0.12316667 -0.6131425 0.3668092 0.7844928
C57-APOE3   -0.03933333 -0.5293092 0.4506425 0.9750839
C57-APOE4    0.08383333 -0.4061425 0.5738092 0.8924974

$`Treatment:Gene`
                                    diff        lwr        upr     p adj
LPS:APOE3-Control:APOE3     -6.126000000 -6.9984204 -5.2535796 0.0000000
Control:APOE4-Control:APOE3 -0.007666667 -0.8800870  0.8647537 1.0000000
LPS:APOE4-Control:APOE3     -6.364666667 -7.2370870 -5.4922463 0.0000000
Control:C57-Control:APOE3   -0.149000000 -1.0214204  0.7234204 0.9910206
LPS:C57-Control:APOE3       -6.055666667 -6.9280870 -5.1832463 0.0000000
Control:APOE4-LPS:APOE3      6.118333333  5.2459130  6.9907537 0.0000000
LPS:APOE4-LPS:APOE3         -0.238666667 -1.1110870  0.6337537 0.9341054
Control:C57-LPS:APOE3        5.977000000  5.1045796  6.8494204 0.0000000
LPS:C57-LPS:APOE3            0.070333333 -0.8020870  0.9427537 0.9997447
LPS:APOE4-Control:APOE4     -6.357000000 -7.2294204 -5.4845796 0.0000000
Control:C57-Control:APOE4   -0.141333333 -1.0137537  0.7310870 0.9929345
LPS:C57-Control:APOE4       -6.048000000 -6.9204204 -5.1755796 0.0000000
Control:C57-LPS:APOE4        6.215666667  5.3432463  7.0880870 0.0000000
LPS:C57-LPS:APOE4            0.309000000 -0.5634204  1.1814204 0.8336034
LPS:C57-Control:C57         -5.906666667 -6.7790870 -5.0342463 0.0000000